Deep learning in human activity recognition with wearable sensors: A review on advances
Mobile and wearable devices have enabled numerous applications, including activity
tracking, wellness monitoring, and human–computer interaction, that measure and improve …
tracking, wellness monitoring, and human–computer interaction, that measure and improve …
Machine learning for microcontroller-class hardware: A review
The advancements in machine learning (ML) opened a new opportunity to bring intelligence
to the low-end Internet-of-Things (IoT) nodes, such as microcontrollers. Conventional ML …
to the low-end Internet-of-Things (IoT) nodes, such as microcontrollers. Conventional ML …
Tinyodom: Hardware-aware efficient neural inertial navigation
Deep inertial sequence learning has shown promising odometric resolution over model-
based approaches for trajectory estimation in GPS-denied environments. However, existing …
based approaches for trajectory estimation in GPS-denied environments. However, existing …
Auritus: An open-source optimization toolkit for training and development of human movement models and filters using earables
Smart ear-worn devices (called earables) are being equipped with various onboard sensors
and algorithms, transforming earphones from simple audio transducers to multi-modal …
and algorithms, transforming earphones from simple audio transducers to multi-modal …
[HTML][HTML] Human activity classification using deep learning based on 3D motion feature
Human activity classification is needed to support various fields. The health sector, for
example, requires the ability to monitor the activities of patients, the elderly, or people with …
example, requires the ability to monitor the activities of patients, the elderly, or people with …
Human action recognition based on a sequential deep learning model
Human Action Recognition (HAR) is an application-oriented field that utilizes numerous
Machine Learning methods to identify diverse human actions or movements to provide an …
Machine Learning methods to identify diverse human actions or movements to provide an …
Summary of the Cooking Activity Recognition Challenge
Abstract Cooking Activity Recognition Challenge [1] is organized as a part of ABC2020 [2]. In
this work, we analyze and summarize the approaches of submissions of the Challenge. A …
this work, we analyze and summarize the approaches of submissions of the Challenge. A …
Experiments on adversarial examples for deep learning model using multimodal sensors
Recently, artificial intelligence (AI) based on IoT sensors has been widely used, which has
increased the risk of attacks targeting AI. Adversarial examples are among the most serious …
increased the risk of attacks targeting AI. Adversarial examples are among the most serious …
Detection and Validation of Macro-Activities in Human Inertial Signals Using Graph Link Prediction
C Wieland, V Pankratius - Sensors, 2024 - mdpi.com
With the continuous development of new wearable devices, sensor-based human activity
recognition is enjoying enormous popularity in research and industry. The signals from …
recognition is enjoying enormous popularity in research and industry. The signals from …
A Combination Model of Shifting Joint Angle Changes With 3D-Deep Convolutional Neural Network to Recognize Human Activity
Research in the field of human activity recognition is very interesting due to its potential for
various applications such as in the field of medical rehabilitation. The need to advance its …
various applications such as in the field of medical rehabilitation. The need to advance its …